Technical Account Manager
At a glance
Manager-level Account Management role at DDN. Santa Clara · full-time · $128,000–$154,000 base.
growthroles summary, based on the employer's posting.
What you'll do
- Set up and tune DDN storage and data-management platforms at customer sites
- Coordinate with customer SRE and operations groups to protect production uptime, capacity and performance
- Use scripts and DevOps utilities to automate system setup, configuration and monitoring
- Diagnose and fix difficult problems involving compute, storage and network layers
- Lead customer technical reviews, document operating practices and channel field requests to product teams
What you bring
- At least eight years doing hands-on systems engineering, deployment or operations work
- A strong Linux administration background and experience running large HPC, AI or ML environments
- In-depth knowledge of parallel file systems such as Exascaler, Lustre or GPFS
- You have configured and diagnosed InfiniBand or high-performance Ethernet networks
- You can automate and monitor with scripting and DevOps tools, including Python, Bash or Ansible
Who this fits
This hands-on role suits someone comfortable working directly with customers and coordinating across operations, engineering and sales. It is hybrid in Santa Clara and involves travel of up to twenty-five percent. Hardware support may require lifting up to seventy-five pounds.
From the employer
Overview
DDN is seeking a Technical Account Manager (TAM) to work directly with strategic enterprise and AI/ML customers, deploying, integrating, and optimizing DDN systems in production environments.
As an TAM, you will serve as the hands-on technical lead responsible for ensuring the success, reliability, and performance of large-scale, globally distributed HPC and AI infrastructure. You’ll act as the bridge between DDN Engineering and customer Site Reliability/Operations teams, translating complex requirements into tested, automated, and maintainable solutions. You will also collaborate with sales and sales engineering teams to develop and optimize offerings to ensure customer success.
Key Responsibilities
Deploy, configure, and optimize DDN storage and data management systems in customer environments.
Partner with customer Site Reliability Engineering (SRE) and Operations teams to ensure production performance, availability, and scalability.
Partner with DDN Sales and Sales Engineering teams to deliver solutions that add value to our customer environments
Automate system monitoring, deployment, and configuration tasks using scripts and DevOps tooling.
Troubleshoot and resolve complex issues across compute, storage, and networking layers.
Develop and maintain deployment documentation, procedures, and best practices.
Work with DDN Engineering and Product Management to translate field requirements into product enhancements (RFEs).
Act as the on-site technical focal point during deployments, upgrades, and critical incidents.
Lead technical meetings and operational reviews with customer and DDN stakeholders.
Drive continuous improvement through feedback loops with Product, Support, and Engineering teams.
Ensure alignment between deployed configurations and customer strategic roadmaps for HPC, AI, and ML workloads.
Required Skills and Experience
8+ years of hands-on technical experience in systems engineering, deployment, or operations.
Strong Linux administration background.
Proven experience deploying and managing large-scale HPC, AI, or ML infrastructure.
Deep knowledge of parallel file systems (Exascaler, Lustre, or GPFS).
Experience configuring and troubleshooting InfiniBand and high-performance Ethernet networks.
Proficiency with DevOps tools and scripting (Python, Bash, Ansible, etc.) for automation and monitoring.
Familiarity with containers, orchestration (Kubernetes, Slurm), and hybrid/cloud environments.
Experience developing and maintaining technical documentation and operational runbooks.
Strong communication skills with the ability to interface directly with customer, engineering and executive teams.
Comfortable working independently in globally distributed environments.
Willingness to travel as required (up to 25%).
Ability to lift up to 75 pounds when supporting hardware installations.
Preferred Qualifications
Experience with AI/ML workflows, GPU-accelerated computing, or large-scale data pipelines.
Familiarity with observability stacks (Prometheus, Grafana, ELK).
Understanding of CI/CD and infrastructure-as-code methodologies.
Project management or DevOps certification (e.g., PMP, CKA, AWS Solutions Architect) is a plus.
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